A Distributed and Collaborative Intelligent System for Medical Diagnosis

Naoufel KHAYATI, Wided LEJOUAD-CHAARI

Abstract


In this paper, we present a distributed collaborative system assisting physicians in diagnosis when processing medical images. This is a Web-based solution since the different participants and resources are on various sites. It is collaborative because these participants (physicians, radiologists, knowledgebasesdesigners, program developers for medical image processing, etc.) can work collaboratively to enhance the quality of programs and then the quality of the diagnosis results. It is intelligent since it is a knowledge-based system including, but not only, a knowledge base, an inference engine said supervision engine and ontologies. The current work deals with the osteoporosis detection in bone radiographies. We rely on program supervision techniques that aim to automatically plan and control complex software usage. Our main contribution is to allow physicians, who are not experts in computing, to benefit from technological advances made by experts in image processing, and then to efficiently use various osteoporosis detection programs in a distributed environment.


Keywords


Program supervisión; Mobile agents; Knowledge model; Ontologies; Medical image analysis; Osteoporosis detection

Full Text:

PDF

References


Benhamou C.L., Harba R., Lespessailles E., Jacquet E., Toulière D. and R. Jennane. Fractal organization of trabecular bone images on calcaneus radiographs, J. Bone Mineral Research, 9:1909-1918, 1994.

Bouhlel N., Hajjaji S., Sevestre S. and Laugier P., Texture analysis using Nakagami-MRF model: Preliminary results on ultrasound images of primary choroidal melanomas. In Proc. of the 16th IEEE International Conference on Image Processing (ICIP 2009), 4181-4184, Cairo, Nov. 2009

Crubézy M., Aubry F., Moisan S., Chameroy V., Thonnat M. and Di Paola, R., Managing complex processing of medical image sequences by program supervision techniques, In Proc. of SPIE Medical Imaging 1997, vol. 3035-85, pp. 614-625, Newport Beach, CA, February 1997

Khayati N., Lejouad-Chaari W., Moisan S. and Rigault J.P., Distributing Knowledge-Based Systems Using Mobile Agents, WSEAS Transactions on Computers, Issue1, Volume 5, pp 22-29; January 2006.

Khayati N, Lejouad-Chaari W, Moisan S. and Rigault J.P, Agent Model for Distributed Program Supervision Systems, The Fifth European Workshop on Multi-Agent Systems - EUMAS'2007, pp 155 164, Hammamet, Tunisia, December 2007.

Khayati N., Lejouad-Chaari W., Sevestre-Ghalila S., A Distributed Interactive Medical Diagnosis Support System, In Proceedings of the 2nd International Conference on Advanced Information and Telemedecine Technologies for Health (AITTH’2008), pp 59-63, Minsk, Belarus, October 2008.

Khayati N., Lejouad-Chaari W., Sevestre-Ghalila S., A Distributed Image Processing Support System: Application to Medical Imaging, In Proceedings of the IEEE International Workshop on Imaging Systems and Techniques (IEEE IST’2008), pp 261-264, Chania, Greece, September 2008.

Khayati N. and Lejouad-Chaari W., Agent and Knowledge Models for a Distributed Imaging System, 10th International Symposium on Distributed Computing and Artificial Intelligence (DCAI’2013), Salamanca, 22-24 mai 2013. Advances in Soft Computing, Springer 2013.

Lejouad-Chaari W, Moisan S, Sevestre-Ghalila S, Rigaut J.P, Distributed Intelligent Medical Assistant for Osteoporosis Detection, In Proc. of the International Conference of IEEE Engineering in Medicine and Biology Society, Lyon – France, August 2007.

Mersal S.S. and Darwish A.M, A new parallel thinning algorithm for gray scale images, IEEE Nonlinear Signal and Image Proc. Conf.,

Antalya, Turkey, June 1999.

Moisan S, Knowledge Representation for Program Reuse, ECAI’02, Lyon. France, Jul. 2002.

Paquet V., Battut P., Blanc H.V. et Ferrand D. On the use of gray run lenth matrices in trabecular bone analysis. In Proc. of the Conf. on the Image Processing and its Application, pages 445-449, July 1995.

Sevestre-Ghalila S., Benazza-Benyahia A., Cherif H. et Souid W., Texture analysis for osteoporosis detection with morphological tools, Medical Imaging 2001, SPIE Conf., Milan Sonka, Kenneth M. Hanson Eds., Vol. 4322, pp. 1534-1541, San Diego, California, USA, 17-23

February 2001.

Sevestre-Ghalila S., Benazza A., Ricordeau A., Mellouli N., Chappard C. et Benhamou C.L., Texture image analysis for osteoporosis detection with morphological tools. In P. Hellier C.Barillot, DR Haynor, editor, MICCAI 2004, volume 1, pages 87-94. LNCS Springer Verlag, September 2004.

Shekhar C., Moisan S. and Thonnat M., Real-Time Perception Program supervision for Vehicle Driving Assistance, In Okyay Kaynak, Mehmed Ozkan, Nurdan Bekiroglu, and Ilker Tunay, editors, ICRAM’95 Intl. Conference on Recent Advances in Mechatronics, pp. 173 179, Istanbul

Thonnat M, Moisan S. and Crubézy M, Experience in Integrating Image Processing Programs, Int. Conf. Vision Systems (ICVS’99). Las Palmas, Spain. January 1999. LNCS 1542, pp 200-215.

Thonnat M. and Moisan S, What can Program Supervision do for Software Reuse?, IEEE Proc. Special Issue on Knowledge Modelling for Software Components Reuse, Vol. 5, No. 147, pp.179- 185, Oct. 2000.

Vincent R., Thonnat M. and Ossola J.C., Program supervision for automatic galaxy classification, In Proc. of the Intl. Conference on Imaging Science, Systems, and Technology, CISST'97, June 1997.

Wigderowitz C.A., Abdel E.W. et Rowley D.L. Evaluation of cancellous structure in the distal radius using spectral analysis. Clin. Orthop., 335:152-161, 1997.




DOI: http://dx.doi.org/10.14201/ADCAIJ201325116





Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.

Clarivate Analytics